Identification of a Nonlinear System by Determining of Fuzzy Rules
Publish Year: 1395
نوع سند: مقاله ژورنالی
زبان: English
View: 318
This Paper With 6 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JIST-4-4_003
تاریخ نمایه سازی: 7 شهریور 1396
Abstract:
In this article the hybrid optimization algorithm of differential evolution and particle swarm is introduced for designing the fuzzy rule base of a fuzzy controller. For a specific number of rules, a hybrid algorithm for optimizing allopen parameters was used to reach maximum accuracy in training. The considered hybrid computational approach includes: opposition-based differential evolution algorithm and particle swarm optimization algorithm. To train a fuzzysystem hich is employed for identification of a nonlinear system, the results show that the proposed hybrid algorithm approach demonstrates a better identification accuracy compared to other educational approaches in identification of thenonlinear system model. The example used in this article is the Mackey-Glass Chaotic System on which the proposed method is finally applied.
Keywords:
Authors
Hodjatollah Hamidi
Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
Atefeh Daraei
Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran